Biocides formulation of essential oils having antimicrobial activity

Essential oils of fennel, peppermint, caraway, eucalyptus, geranium and lemon were tested for their antimicrobial activities against some plant pathogenic micro-organisms (Fusarium oxysporum, Alternaria alternate, Penicilium italicum Penicilium digitatum and Botyritus cinerea). Essential oils of fennel, peppermint, caraway were selected as an active ingredient for the formulation of biocides due to their efficiency in controlling the tested micro-organisms. Successful emulsifiable concentrates (biocides) were prepared from these oils using different emulsifiers (Emulgator B.L.M. Tween20 and Tween80) and different fixed oils (sesame, olive, cotton and soybean oils). Physico-chemical properties of the formulated biocide (spontaneous emulsification, emulsion stability test, cold stability and heat stability tests as well as viscosity, surface tension and pH) were measured. The prepared biocides were ready to be tested for application in a future work as a safe pesticide against different pathogens.     

Book reviews

John B. Boles (ed.), MASTERS AND SLAVES IN THE HOUSE OF THE LORD: RACE AND RELIGION IN THE AMERICAN SOUTH, 1740–1870, Lexington, KY: The University of Kentucky Press, 1988, 257 pp.

David E. Swift, BLACK PROPHETS OF JUSTICE: ACTIVIST CLERGY BEFORE THE CIVIL WAR, Baton Rouge, Louisiana, LA: Louisiana State University Press, 1989, xv + 384 pp., £31.50.

Alexander B. Murphy, THE REGIONAL DYNAMICS OF LANGUAGE DIFFERENTIATION IN BELGIUM: A STUDY IN CULTURAL‐POLITICAL GEOGRAPHY, Chicago, IL: University of Chicago, Geography Research Paper No. 227, 1988, xiii + 249 pp., $12.00.

Pierre L. van den Berghe, STRANGER IN THEIR MIDST, Denver, CO: University Press of Colorado, 1989, xvii + 300 pp., $24.95.     

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.     

Seasonal dimorphism in the horny bills of sparrows

Bill size is often viewed as a species‐specific adaptation for feeding, but it sometimes varies between sexes, suggesting that sexual selection or intersexual competition may also be important. Hypotheses to explain sexual dimorphism in avian bill size include divergence in feeding niche or thermoregulatory demands, intrasexual selection based on increased competition among males, or female preference. Birds also show seasonal changes in bill size due to shifts in the balance between growth rate and wear, which may be due to diet or endogenous rhythms in growth. Insight into the function of dimorphism can be gained using the novel approach of digital x‐ray imaging of museum skins to examine the degree to which the skeletal core or the rhamphotheca contribute to overall dimorphism. The rhamphotheca is ever‐growing and ever‐wearing, varying in size throughout life; whereas the skeletal core shows determinant growth. Because tidal marsh sparrows are more dimorphic in bill size than related taxa, we selected two marsh taxa to investigate dimorphism and seasonality in the size of the overall bill, the skeletal core, and the rhamphotheca. Bill size varied by sex and season, with males having larger bills than females, and bill size increasing from nonbreeding to breeding season more in males. Skeletal bill size varied with season, but not sex. The rhamphotheca varied primarily with sex; males had a larger rhamphotheca (corrected for skeletal bill size), which showed a greater seasonal increase than females. The rhamphotheca, rather than the skeletal bill, was responsible for sexual dimorphism in overall bill size, which was particularly well developed in the breeding season. The size of the rhamphotheca may be a condition‐based character that is shaped by sexual selection. These results are consistent with the evidence that bill size is influenced by sexual selection as well as trophic ecology.     

Obesity and early mortality in the United States

Objective:

Although obesity is a serious public health problem, there are few reliable measures of its health hazards in the United States. The objective of this study was to estimate how much earlier mortality is likely to occur for Americans who are obese (body mass index [BMI], ≥ 30).

Design and Methods:

Data from the National Health and Nutrition Examination Survey (NHANES) I (1971–1975), NHANES II (1976–1980), and NHANES III (1988–1994) for 37,632 participants who experienced 8,791 deaths during 15 years of follow‐up were prospectively analyzed. The relative risk of death from all causes and its advancement period, adjusted for covariates, were calculated. Stratification was used to investigate the effects of pre‐existing illness, smoking, and older age on the advancement period.

Results:

Compared to the participants of reference weight (BMI, 23 to <25 kg/m2), mortality was likely to occur 9.44 years (95% confidence interval [CI]: 0.72, 18.16) earlier for those who were obese (BMI, ≥ 30). For overweight (25 to <30 kg/m2), grade 1 obesity (BMI, 30 to <35) and grades 2–3 obesity (BMI, ≥ 35.0), the mortality was likely to occur earlier by 4.40 (?3.90, 12.70), 6.69 (?2.06, 15.43), and 14.16 (3.35, 24.97) years, respectively. These estimates apply to healthy nonsmoker young‐ and middle‐aged (21–55 years) adults, who constituted an estimated 32.8% of Americans with age of >21 years between 1988 and 1994. Without stratifying simultaneously for preexisting illness, smoking, and age, values of the advancement period for obesity were markedly smaller than those observed for healthy nonsmoker young and middle‐aged adults.

Conclusions:

For healthy nonsmokers young‐ and middle‐aged adults who constitute about one‐third of American adults, being obese is likely to hasten mortality by 9.44 years.

     

Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models

Detecting gene-gene interaction in complex diseases has become an important priority for common disease genetics, but most current approaches to detecting interaction start with disease-marker associations. These approaches are based on population allele frequency correlations, not genetic inheritance, and therefore cannot exploit the rich information about inheritance contained within families. They are also hampered by issues of rigorous phenotype definition, multiple test correction, and allelic and locus heterogeneity. We recently developed, tested, and published a powerful gene-gene interaction detection strategy based on conditioning family data on a known disease-causing allele or a disease-associated marker allele⁴. We successfully applied the method to disease data and used computer simulation to exhaustively test the method for some epistatic models. We knew that the statistic we developed to indicate interaction was less reliable when applied to more-complex interaction models. Here, we improve the statistic and expand the testing procedure. We computer-simulated multipoint linkage data for a disease caused by two interacting loci. We examined epistatic as well as additive models and compared them with heterogeneity models. In all our models, the at-risk genotypes are “major” in the sense that among affected individuals, a substantial proportion has a disease-related genotype. One of the loci (A) has a known disease-related allele (as would have been determined from a previous analysis). We removed (pruned) family members who did not carry this allele; the resultant dataset is referred to as “stratified.” This elimination step has the effect of raising the “penetrance” and detectability at the second locus (B). We used the lod scores for the stratified and unstratified data sets to calculate a statistic that either indicated the presence of interaction or indicated that no interaction was detectable. We show that the new method is robust and reliable for a wide range of parameters. Our statistic performs well both with the epistatic models (false negative rates, i.e., failing to detect interaction, ranging from 0 to 2.5%) and with the heterogeneity models (false positive rates, i.e., falsely detecting interaction, ≤1%). It works well with the additive model except when allele frequencies at the two loci differ widely. We explore those features of the additive model that make detecting interaction more difficult. All testing of this method suggests that it provides a reliable approach to detecting gene-gene interaction.     

Cell separation mediated by differential rolling adhesion

Recently, we showed a correlation between the maturity of hematopoietic stem and progenitor cells during development and rolling efficiency on selectins. These findings motivated us to explore a novel separation that exploits differences in selectin-mediated rolling adhesion between populations of cells. We extend the use of a previously developed cell-free system to study the separation of populations of sialyl Lewis x (sLe(x))-coated microspheres designed to roll with different average velocities on L-selectin chimeric substrates under well-defined flow. Results show that a separation that exploits differences in average rolling velocities between cell or microsphere populations is attainable. Excellent recovery and purity values for the slower rolling, or more desirable, populations are obtained and can be estimated from rolling velocity measurements. We also assess the feasibility of a selectin-mediated separation of adult bone marrow cell populations using previously obtained rolling velocity and rolling flux data for CD34+ and CD34- adult bone marrow cells on L-selectin substrates. We believe that a cell separation mediated by differential rolling adhesion can be used to enrich populations of hematopoietic stem and progenitor cells from an adult bone marrow cell preparation and that this method possesses several major advantages over existing antibody-mediated cell-affinity chromatography technologies.